Integrating experiments, numerical simulations and clinical exams for patient-specific hemodynamic analyses

  • Mariotti, Alessandro (DICI - Univesity of Pisa)
  • Morello, Mario (DICI - Univesity of Pisa)
  • Singh, Jaskaran (DICI - Univesity of Pisa)
  • Vignali, Emanuele (BioCardioLab - Heart Hospital, Massa)
  • Gasparotti, Emanuele (BioCardioLab - Heart Hospital, Massa)
  • Salvetti, Maria Vittoria (DICI - Univesity of Pisa)
  • Celi, Simona (BioCardioLab - Heart Hospital, Massa)

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In the context of digital transition in the clinical environment, augmented digital twin models may be employed, in which the raw clinical data are integrated and augmented with the results from Computational Fluid Dynamic (CFD) and Fluid-Structure simulations, in order to obtain reliable predictors of possible pathology development or progression. The aim our research activity is the merging of CFD simulations with in-vivo data (MRI or CT) to provide detailed and reliable clinical information at a patient-specific level. In-vivo measurements may provide the patient-specific boundary conditions for the simulations and give data for the validation of numerical results, but both MRI and CT suffer from limitations in the spatial and temporal resolution limitations that can be achieved and these techniques are not able to accurately provide quantitative flow descriptors, such as the wall shear stresses. On the other hand, CFD simulations allow the flow and pressure fields to be investigated with space and time resolutions that are not achievable by any in-vivo measurement, but the accuracy of CFD predictions strongly depends not only on the need for accurate input data but also on modeling assumptions and computational set-up. Sources of uncertainties are for example inlet and outlet boundary conditions or the vessel mechanical properties for fluid-structure interaction. Since some of these uncertain features are difficult to be completely characterized and/or controlled in in-vivo data, the simulations are compared also with in-vitro data obtained by a fully-controlled and sensor-equipped circulatory mock loop for 3D-printed aortic models. In this experimental set-up, the flow rate is perfectly controlled, the model is fixed, and the wall model properties are known. In this way, clearer indications can be obtained to assess and possibly improve the accuracy of CFD models (vs. in-vitro data) and to single out the importance of the differences between in-vivo and in-vitro set-ups. In the presentation, patient-specific simulations and experiments of healthy and diseased aortas and carotid arteries will be compared.